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    Investigating cooked rice textural properties by instrumental measurements

    2020-05-22 03:29:40KeyuTaoWenwenYuSangeetaPrakashRobertGilbert

    Keyu Tao,Wenwen Yu,Sangeeta Prakash,Robert G.Gilbert,e,*

    a Joint International Research Laboratory of Agriculture and Agri-Product Safety,College of Agriculture,Yangzhou University,Yangzhou,Jiangsu,225009,PR China

    b The University of Queensland,Centre for Nutrition and Food Sciences,Queensland Alliance for Agriculture and Food Innovation,Brisbane,QLD,4072,Australia

    c Department of Food Science&Engineering,Jinan University,Huangpu West Avenue 601,Guangzhou City,Guangdong Province,510632,PR China

    d The University of Queensland,School of Agriculture and Food Science,QLD,4072,Australia

    e Jiangsu Key Laboratory of Crop Genetics and Physiology,Key Laboratory of Plant Functional Genomics of the Ministry of Education,Jiangsu Key Laboratory of Crop Genetics and Physiology,College of Agriculture,Yangzhou University,Yangzhou,225009,PR China

    ABSTRACT Foods wherein the starch is slowly digested contribute to good health by reducing the tendency to,and for the maintenance of,diabetes,obesity and colo-rectal cancers.While foods with high amylose content have this desirable property,they usually do not have high sensory appeal and consumers are reluctant to eat them.While sensory evaluation by trained human panelists is the best way to obtain consumer preferences,these tests are expensive,time-consuming and require considerable effort and care.Instrumental measurements are easier,cheaper and invaluable for screening,but only useful if they correlate with human data for the type of food being considered.Here,we test this using cooked rice with a wide range of amylose contents.Functional properties were correlated against quantitative descriptive panelist analysis.Swelling power and breakdown viscosity correlated with all panelist sensory attributes,but no other correlations with gelatinization properties were observed.There was a strong correlation between hardness and stickiness measured by texture profile analysis(TPA)and by panelists,suggesting that TPA can be used to measure hardness and stickiness of cooked rice.We also showed that breakdown viscosity is a reliable instrumental means to provide indicative measurements of hardness and rice preference,and swelling power is a predictor of rice stickiness.

    Keywords:Rice Texture Instrumental Viscosity Swelling power

    1.Introduction

    Rice provides energy and nutrients for half of the world’s population.Cooked rice sensory quality,the main property in determining consumer acceptance and market price of a rice variety,is affected by multiple factors including protein [1],lipids[2],amylose/amylopectin ratio [1],color of cooked rice kernels[3]and cooking methods [4].Starch is the main component of rice endosperm and comprises up to about 90% (dry weight) of rice kernels.Cooked white rice is rapidly digested to glucose in the gastrointestinal tract,which is undesirable from the point of view of human wellness:it is deleterious with regards to prevention and maintenance of diabetes,obesity and colo-rectal cancers.While high-amylose rice is slowly digested,it is less palatable especially when prepared by common cooking methods such as a rice cooker [5].Most people generally will not eat something they dislike,and thus high-amylose rice is not well accepted by most consumers.Sensory evaluation conducted by experienced panelists is by far the best means of predicting consumer preferences.However,this is time-consuming,expensive,laborious,requires rigorous experimental protocols and involves great care and effort for reproducibility.In addition,sensory preferences vary with cultural differences [6].Instrumental methodologies haveadvantages if they can be proven to give reliable and robust correlations with panelist data for the type of food under consideration.For instance,Wee et al.[7]reported that data(mainly springiness and cohesiveness) for a wide range of foods measured by textural profile analysis (TPA) have statistically significant correlations with panelist results.It also has been found that cooked rice textural parameters are significantly correlated with sensory evaluation results[8].

    Table1 Rice varieties and rice-to-water weight ratios1.

    As well as being time-consuming,cooked rice texture measurements by TPA are subject to variation in the rice kernels chosen and temperature control,and thus require extensive repetition.Quicker,more stable and reliable methods to predict sensory evaluation results are needed.The properties of cooked rice kernels and rice flour are mainly controlled by rice starch structural features.This suggests that appropriate physicochemical properties of rice flour,including pasting properties measured by rapid viscoanalysis (RVA),and gelatinization properties measured by differential scanning calorimetry (DSC),may also significantly correlate with cooked rice sensory properties.For example,the RVA peak viscosity and breakdown viscosity have been found to be significantly negatively correlated with cooked rice hardness[9].It has been reported[10]that setback viscosity was either positively or negatively correlated with textural attributes.In addition,RVA parameters have been found to be highly correlated with overall acceptability[11].Panelists preferred rice with lower final viscosity (FV) as well as setback viscosity (SBV).It has been reported that the consistency coefficient of rice flour(K*)from a dynamic frequency sweep using a rheometer could be used to express cooked rice hardness while tan δ can be used to express stickiness[8].Using data from trained human panelists [12],we have reported that among commonly accepted rice sensory attributes (stickiness,roughness,hardness,cohesiveness,toothpack,dryness,and residual rice remaining in mouth after swallowing),hardness is the most important factor determining overall panelist preferences.Some work has been done on predicting rice eating quality with multiple characteristics,including appearance,aroma,composition and texture,as measured by instruments or by a panel[3,13].

    None of those studies,however,systematically compared results from textural instrument measurements and from panelists.No widely-accepted agreement has yet been reached on the question of panelist/instrumental correlation.The present study aims to clarify this problem by investigating which properties correlate well with quantitative descriptive analysis for cooked rice.It differs from previous studies in that the rice samples used here have a wide range of amylose content,which is important nutritionally(high-amylose starches are generally slower to digest,which is nutritionally advantageous).

    This provides information for the development of suitable instrumental methodologies to evaluate and to predict cooked rice textural properties,which although never able to completely replace data from human panelists,can be useful for purposes such as preliminary screening.

    2.Materials and methods

    2.1.Materials

    The present study uses the same samples as in previously published work [12].As amylose content is an important factor for the cooking and human-wellness quality of a rice,the previously reported values are repeated here along with rice varieties in Table1.De-husking,polishing and grinding were as described previously[12].

    2.2.Swelling power of whole-grain rice flour

    The swelling power of whole-grain rice flour was measured using the method described by Adebooye and Singh[14]with modifications.Fifty mg rice flour and 1 mL water were heated at 90°C for 10 min.The slurry was then cooled in iced water for 5 min followed by centrifuging at 7000 ×gfor 15 min,and the supernatants discarded.The wet precipitate was freeze-dried to constant weight.Swelling power was found as the ratio of wet sediment to freeze-dried sample weights.

    2.3.Pasting properties of whole-grain rice flour

    Pasting properties of rice flour were determined using a rapid viscosity analyzer (RVA,Newport Scientific,Warriewood,NSW,Australia).Exactly 2 g starch and 25 mL water were weighed into the RVA chamber and equilibrated at 50°C for 60 s before heating to 95°C over 4 min.Sample was maintained at 95°C for 2 min,then cooled down to 50°C within 4 min,and held at 50°C for 2 min.The paddle speed was set at 160 r/min during the whole measurement.The peak,trough,final,breakdown and setback viscosities were measured.

    2.4.Gelatinization properties of whole-grain rice flour

    The gelatinization properties of rice flour were analyzed by DSC(DSC 25,TA) using a method described previously [15].Four mg of rice flour and 8 mg H2O were weighed into an aluminium crucible and sealed.After equilibrating at room temperature for 1 h,the crucible was heated from 20°C to 110°C at 10°C/min.The data obtained comprise the onset temperature(To),peak temperature(Tp),conclusion temperature(Tc)and crystal melting enthalpy(ΔH).

    Table2 Physicochemical and pasting properties of rice flour and textural properties of cooked rice1.

    2.5.Textural measurement of cooked rice by TPA and sensory panelists

    Rice texture measurement was performed according to a method given elsewhere [16]with minor modifications.White rice was rinsed with distilled water three times to remove adhering substances.Rice kernels and distilled water were placed in an automated electric rice cooker (Target,China) with different riceto-water weight ratios depending on amylose content,as listed in Table1.Cooking was for about 10-15 min (as controlled by the automated rice cooker),followed by a 10 min holding period in warm mode.Cooked rice was gently mixed after discarding the top layer of rice and rice adhering to the walls of the rice cooker.Cooked rice was kept in a 50°C water bath and covered with food cling wrap until analysis.

    After cooling down to room temperature,three cooked rice kernels were positioned centrally under a probe on the base plate.Textural attributes were analyzed by a TA-XT plus Texture Analyzer(Stable Microsystems,UK)with a 35 mm Cylinder Probe using a two-cycle,force-versus-distance compression program.The TPA settings were as follows:Pre-Test Speed,0.5 mm/s; Test Speed,0.5 mm/s; Post-Test Speed,2.00 mm/s; Strain,90%; Time,5.00 s;Trigger Force (auto),0.05 N.Fifteen texture measurements were conducted for each rice.The maximum compression force on the first cycle (hardness) and the negative force area of the first cycle(stickiness) were computed with Exponent Stable Micro Systems software.

    The panelist sensory measurements used here are those reported previously [12],with a panel of 5 males and 5 females,all from China and all resident in Brisbane,Australia,for at least one year at the time of the tests.Eight sensory descriptive texture attributes,including stickiness,roughness,hardness,cohesiveness,toothpack,dryness and residual rice,were adapted from Bett-Garber et al.[17].Quantitative descriptive analysis?(QDA) was used to generate cooked rice sensory profiles,and acceptability was assessed by the consumer acceptance test[5]conducted separately as an independent test.Twelve hours training sessions were conducted to enable panelists gain familiarity in recognizing each attribute and to develop individual discriminating ability with various references and commercial rice samples.During training sessions,duplicate samples were scored for all attributes,to monitor panel reproducibility.When the panel performance was consistent,participants were taken to individual booths,and they then evaluated final test samples.The evaluation of final samples was done in duplicate to make sure that the data as reliable as possible.Due to the limited number of panelists participating in the acceptability test,only a semi-quantitative indication of preference was obtained in this study.

    2.6.Statistical analysis

    Mean value and standard deviations were calculated by SPSS 20.0 statistical software (Statistical Graphics Corp.,Princeton,NJ).Significant difference analysis was carried outusing analysisofvariance(ANOVA)with Tukey pairwise comparisons(P<0.05).Pearson correlation was obtained using SPSS 20.0 statistical software(Statistical Graphics Corp.,Princeton,NJ).Principal component analysis(PCA)was plotted using XLSTAT.

    3.Results and discussion

    3.1.Cooked rice texture,swelling power and pasting properties of rice flour

    The textural properties of cooked rice kernels (hardness and stickiness)measured by TPA are listed in Table2.Consistent with previous reports [18],the higher the amylose content,the firmer and less sticky the rice:lower amylose content tended to result in greater hydration of rice,finally leading to softer and stickier rice.

    Results for the panel texture evaluation have been reported previously [12]and are repeated here in TableS1 in Supporting Information,with the addition of standard deviations.The attributes measured were stickiness,roughness,hardness,cohesiveness,toothpack,dryness,residual rice and panelist preference.In general,stickiness intensity decreased and hardness intensity increased with increasing amylose content.Sample 491,with the lowest amylose content(approximately 2%),had the highest stickiness,cohesiveness and toothpack attributes,while sample 326(highest amylose content,approximately 31%)had the highest levels of roughness,hardness,dryness and residual rice.

    Table2 also shows the swelling power and pasting properties of rice flour.The swelling power generally decreased with increased amylose content,but not uniformly so.This supports findings that amylose content alone is insufficient to explain the decreased swelling power with increased amylose content [15].The pasting profiles of these native rice flours are summarized in Table2.Sample 491 (waxy rice) had the lowest setback viscosity.Sample 326 with highest amylose content had the lowest peak,trough,final and breakdown viscosities.While all vary with amylose content,there was no systematic trend:again,amylose content is not the sole factor.Other components like rice protein and starch fine structure can also influence swelling power and pasting properties.For example,it has been found that the ratio of total prolamin:total prolamin+total glutelin in rice was positively associated with setback viscosity[19].RVA setback viscosity is determined both by the amylose content and the amount of long amylose chains[15].

    Table3 Gelatinization properties of rice flour1.

    Table4 Pearson correlation between textural parameters measured by TPA(present study)and by panelists[12],and swelling power,pasting and gelatinization of rice flour(n=11).PV=peak viscosity,TV=trough viscosity,FV=final viscosity,BD=breakdown viscosity,SBV=setback viscosity.

    Although significant positive correlations between gelatinization temperature and amylose content have been observed in other cereals,such as barley flour [20]this was not the case here,as shown in Table3.The gelatinization enthalpy has been reported to increase with decreasing amylose content [15].Interestingly,rice 491,which has the lowest amylose content,has significantly lower crystal melting enthalpy(ΔH)than that of rices 712 and 868,as well as onset temperature (To),peak temperature (Tp) and conclusion temperature(Tc).

    3.2.Correlations between sensory properties and instrumental data

    The panelist sensory evaluation results used here are those reported previously [12].There is no significant correlation between rice flour gelatinization properties and the sensory attributes measured by either panelists or TPA,as seen in Table4.However,positive correlation between enthalpy and the hardness of cooked noodles after storage has been observed,which may result from the retrogradation of starch [21].Rice flour pasting properties have been used extensively to predict cooked rice texture properties; however,among pasting properties of rice flour measured using RVA,the only significant correlations seen here were between the breakdown viscosity and all sensory attributes(Table4).In detail,the breakdown viscosity is significantly positively correlated with stickiness,cohesiveness,toothpack and also panelist preferences,but negatively correlated with hardness,roughness,dryness and residual rice.It should be noted that the preference study was conducted separately to gain a qualitative indication among the rice varieties investigated in this study.However,it was reported that setback viscosity was either positively or negatively related with texture attributes,and breakdown viscosity was only correlated to hardness [10].This difference may result from the samples chosen.A wider range of amylose content rice was chosen in this study than previously studied(the previous widest being from Champagne et al.[22],with amylose content of 10%-25%).

    The correlation between swelling power and panelist sensory attributes is similar to those between breakdown viscosity and sensory attributes.It was found in this study that,except for preference,all texture attributes measured by panelists (hardness,stickiness,cohesiveness,toothpack,dryness,roughness,residual rice)significantly correlated with swelling power.This indicates that the swelling power of rice flour can also be used to predict cooked rice textural properties.

    Stickiness and hardness are the two most important texture attributes.As shown in Table4 and Fig.1,significant positive correlations are seen between stickiness measured by TPA and stickiness scored by panelists (correlation coefficient 0.85),while hardness from TPA is also significantly and positively correlated with sensory hardness(correlation coefficient 0.87).This demonstrates that the instrumental measurements by TPA can reflect human perceptions in cooked rice texture test.In the following,all hardness and stickiness parameters are those from TPA,unless indicated otherwise.

    Fig.1.Correlation between stickiness as judged by sensory panel and as measured by TPA.Sample number indicated for each point.

    Fig.2.Principal component analysis of the instrumental measurement results.Sample codes are in red.Amylose content in brackets.

    In order to explore the textural attributes of cooked rice and the functional properties of rice flour,data were analyzed using principal component analysis(PCA).As there were no statistically significant correlations between gelatinization properties measured by DSC and any cooked rice textural attributes(Table3),PCA bi-plots only included pasting properties,TPA texture results and swelling power,as shown in Fig.2.The two principal components explain a total of 88.86% of the variation with the first principal component 1 (PC1) and the second principal component 2 (PC2),explaining 45.39% and 43.47% of the variation,respectively.The cooked rice hardness measured by TPA is on the top left of PC1,indicating that hardness is significantly negatively associated with stickiness,swelling power and breakdown viscosity,which are all on the bottom right of PC1.The angle between the vector of hardness and that of breakdown viscosity is the largest,close to 180°,indicating that hardness shows a stronger negative correlation with breakdown viscosity.It suggests that breakdown viscosity can be used as a good(negative)predictor of cooked rice hardness.It has been reported that compared with other rice textural characteristics,hardness from TPA shows the strongest correlation(negative)with cooked rice eating quality determined by Korean panelists[3].A similar correlation was also seen when conducted with Chinese panelists,which indicates hardness is the dominant rice eating quality[12].This suggests that breakdown viscosity may be indeed used to predict the eating quality of cooked rice.

    Positive correlations were observed between stickiness,swelling power and breakdown viscosity.Among these three parameters,swelling power and stickiness almost overlap with each other in the PCA plot,as shown in Fig.2.This further supports the inference that cooked rice stickiness could be predicted through measuring the swelling power of native rice flour.

    The instrumental data reported here are correlated with the starch molecular structural data reported previously [12]; the results are given in Supporting Information.These are consistent with much more extensive correlations reported in the literature.

    4.Conclusions

    This paper examines of using physicochemical properties of rice flour and instrumental methodologies (TPA,RVA and DSC) to correlate with cooked rice sensory properties measured by panelists,with the samples used having a wide range of amylose content.It is found that both swelling power and the breakdown viscosity of rice flour can be used to predict textural properties of cooked rice,especially stickiness and hardness,which are the most important sensory attributes.Breakdown viscosity is also a(positive) predictor of rice preference (for the panel used here).As preference depends on culture,the result may change if different ethnic and racial groups are chosen.This is useful information for the development of instrumental methods to give indicative data for the prediction of cooked rice textural properties,thereby providing useful information for use of instrumental methods for purposes,such as screening,prior to final evaluation by human sensory panelists.This is especially important for rices with varying amylose content,because amylose content is generally associated with slower digestibility(which is nutritionally advantageous)but this is by no means the only criterion,and sensory data are essential to find varieties that are both acceptable to consumers while also having this aspect of nutritional benefit.

    Declaration of Competing Interest

    The authors declare no competing interests.

    Acknowledgements

    We gratefully acknowledge the support of a National Science Foundation of China grant C1304013151101138 and of the 2017 Jiangsu Innovation and Entrepreneurship talents program(to R.G.G.).A project funded by the Priority Academic Program of Jiangsu Higher Education Institutions.We also gratefully acknowledge Dr.Jixun Luo (CSIRO Plant Industry,Australia) and the New South Wales(Australia)Department of Primary Industries for providing rice samples.

    Appendix A.Supplementary data

    Supplementary material related to this article can be found,in the online version,at doi:https://doi.org/10.1016/j.fshw.2020.02.001.

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